Contrarian Signals – market sentiment indicators

Hacker News

A dashboard of market sentiment indicators deliberately biased towards the opposite of whatever the crowd is doing right now. This was also partly motivated by wanting to play with terminal aesthetics and dense user interfaces. Indicators: CNN Fear&Greed, Put/Call ratio, AAII Sentiment Survey, BofA Sell-side indicator, among others — feedback appreciated on potential signals to track! Disclaimer: this was ~70% vibe coded using Cursor / Claude Code. Link: https://contrariansignals.com (free to access, subscription required to get daily alerts)

Visit product View on Hacker NewsNov 24, 2025

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: cursor, claude, user · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

19%19% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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